REALCLIMATE REPORTS :
The 5th International Conference on Regional Climate
The fifth international conference on regional climate (ICRC 2023), organised by World Climate Research Programme's (WCRP) coordinated downscaling experiment (CORDEX), has just completed. It was a hybrid on-site/online conference with hubs in both Trieste/Italy (hosted by the International Centre on Theoretical Physics, ICTP) and Pune/India. The hybrid set-up, with video links between the two … Read Full Article
Provision of climate information to society
One session was devoted to the interaction with society. To me, it seems that CORDEX is not yet ready to provide society with robust and actionable information, despite the initiative from the WCRP called regional information for society (RIfS).
RIfS has taken a long time since it was conceived in 2020 (my impression is that it’s still not ready). There is an urgency underscored by the numerous reports of weather-related calamities around the world – we are not even adapted to the current climate and a newsreport from Washington Post reveals that 2023 September month global mean temperature was probably about 1.7°C above the preindustrial level.
There is a WCRP Open Science Conference (OSC 2023) in Kigali October 23-27 where RIfS probably will be discussed further, but it’s not clear to me what it’s all about or who is involved. My impression is that the WCRP and RIfS have closer links to more academic university communities than for instance more applied and operational national meteorological services.
Many national meteorological services have already established routines and are experienced in providing regional weather and climate information to society.
For instance, the Norwegian Meteorological Institute collaborates with various institutions and authorities, such as the Norwegian Water Resources and Energy Directorate (NVE), the Norwegian Institute of Public Health (NIPH), the Norwegian Directorate for Civil Protection, power production (StatKraft) and grid (Statnett), road authorities, aviation, rail, and defense. Our experience is that relevant information flows quite well within such a professional network.
Climate services in Norway differ from weather forecasting as they aim at the municipalities and need to reach local engineers and policymakers. There are other hurdles that need to be overcome when establishing new routines compared to state authorities.
For instance, small municipalities typically lack resources, the know how and incentives. They often have set protocols and routines that are not designed to accommodate climate change adaptation.
Typical topics include water management and area planning. A unique approach in Norway is to channel climate information through the trade union for civil engineers, Tekna (which is both a professional society and a trade union), e.g. through professional courses.
The meteorological service also has some experience with impact studies and we have collaborated on e.g. toxicology (SETAC), health, biology, national heritage, indigenous people (reindeer herders), and disaster risk reduction (e.g. flooding, earth-slides). So even if the progress is slow with RIfS, there is plenty of activities on applied research relevant for society.
Some self criticism
A remark made during the ICRC made me wonder about the question: Would our regional climate modelling community benefit from more critical reflections and discussion about what we should avoid?
My impression is that there are some cases of flawed use of downscaling that we don’t call out often enough. Nevertheless, it’s necessary to be extra critical and quizzical when our results are used for climate change adaptation and impact studies in order to avoid maladaptation and misleading impact studies.
One message that I tried to remind my colleagues is that everybody, who downscales global climate model output for use as regional and local climate projections, must read Deser et al. (2012) and account for random regional climate variations on scales up to decades.
There are too many examples of regional and local climate projections based on one or a small number of global climate model simulations. The “law of small numbers” implies a minimum number of independent simulations in an ensemble (Rabin, 2002).
If one picks the results from one climate model one gets a projection, but if one were to chose another computation from the very same model, then the projection would look quite different.
The difference is due to the chaotic nature of natural regional climate variations. But if we estimate statistics (e.g mean or probability distribution/histogram) on say 100 simulations, then such statistics won’t be much affected if we were to change one or some of the model simulations. This is what we mean by robust results and it’s also useful that statistical properties often are more predictable than individual outcomes.
